<!-- This comment will put IE 6, 7 and 8 in quirks mode -->
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/>
<title>include/shark/ObjectiveFunctions/LooError.h Source File</title>
<script type="text/javaScript" src="search/search.js"></script>
<script type="text/javascript" src="jquery.js"></script>
<script type="text/javascript" src="dynsections.js"></script>
<script src="https://polyfill.io/v3/polyfill.min.js?features=es6"></script>
<script id="MathJax-script" async src="https://cdn.jsdelivr.net/npm/mathjax@3.0.1/es5/tex-mml-chtml.js"></script>
<script src="../../mlstyle.js"></script>
<link href="../css/besser.css" rel="stylesheet" type="text/css"/>
</head>
<!-- pretty cool: each body gets an id tag which is the basename of the web page  -->
<!--              and allows for page-specific CSS. this is client-side scripted, -->
<!--              so the id will not yet show up in the served source code -->
<script type="text/javascript">
    jQuery(document).ready(function () {
        var url = jQuery(location).attr('href');
        var pname = url.substr(url.lastIndexOf("/")+1, url.lastIndexOf(".")-url.lastIndexOf("/")-1);
        jQuery('#this_url').html('<strong>' + pname + '</strong>');
        jQuery('body').attr('id', pname);
    });
</script>
<body>
    <div id="shark_old">
        <div id="wrap">
            <div id="header">
                <div id="site-name"><a href="../../sphinx_pages/build/html/index.html">Shark machine learning library</a></div>
                <ul id="nav">
                    <li >
                        <a href="../../sphinx_pages/build/html/rest_sources/installation.html">Installation</a>
                    </li>
		    <li >
                        <a href="../../sphinx_pages/build/html/rest_sources/tutorials/tutorials.html">Tutorials</a>
                    </li>
		    <li >
                        <a href="../../sphinx_pages/build/html/rest_sources/benchmark.html">Benchmarks</a>
                    </li>
                    <li class="active">
                        <a href="classes.html">Documentation</a>
                        <ul>
                            <li class="first"></li>
                            <li><a href="../../sphinx_pages/build/html/rest_sources/quickref/quickref.html">Quick references</a></li>
                            <li><a href="classes.html">Class list</a></li>
                            <li class="last"><a href="group__shark__globals.html">Global functions</a></li>
                        </ul>
                    </li>
                </ul>
            </div>
        </div>
    </div>
<div id="doxywrapper">
<!--
    <div id="global_doxytitle">Doxygen<br>Documentation:</div>
-->
    <div id="navrow_wrapper">
<!-- Generated by Doxygen 1.9.8 -->
<div id="nav-path" class="navpath">
  <ul>
<li class="navelem"><a class="el" href="dir_d44c64559bbebec7f509842c48db8b23.html">include</a></li><li class="navelem"><a class="el" href="dir_9d0c4981f10d03078bcfd5c74fe41ce8.html">shark</a></li><li class="navelem"><a class="el" href="dir_1791956e1c2f180e4a35bcf03083ac8e.html">ObjectiveFunctions</a></li>  </ul>
</div>
</div><!-- top -->
<div class="header">
  <div class="headertitle"><div class="title">LooError.h</div></div>
</div><!--header-->
<div class="contents">
<a href="_loo_error_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a id="l00001" name="l00001"></a><span class="lineno">    1</span><span class="comment">/*!</span></div>
<div class="line"><a id="l00002" name="l00002"></a><span class="lineno">    2</span><span class="comment"> * </span></div>
<div class="line"><a id="l00003" name="l00003"></a><span class="lineno">    3</span><span class="comment"> *</span></div>
<div class="line"><a id="l00004" name="l00004"></a><span class="lineno">    4</span><span class="comment"> * \brief       Leave-one-out error</span></div>
<div class="line"><a id="l00005" name="l00005"></a><span class="lineno">    5</span><span class="comment"> * </span></div>
<div class="line"><a id="l00006" name="l00006"></a><span class="lineno">    6</span><span class="comment"> * </span></div>
<div class="line"><a id="l00007" name="l00007"></a><span class="lineno">    7</span><span class="comment"> *</span></div>
<div class="line"><a id="l00008" name="l00008"></a><span class="lineno">    8</span><span class="comment"> * \author      T.Glasmachers</span></div>
<div class="line"><a id="l00009" name="l00009"></a><span class="lineno">    9</span><span class="comment"> * \date        2011</span></div>
<div class="line"><a id="l00010" name="l00010"></a><span class="lineno">   10</span><span class="comment"> *</span></div>
<div class="line"><a id="l00011" name="l00011"></a><span class="lineno">   11</span><span class="comment"> *</span></div>
<div class="line"><a id="l00012" name="l00012"></a><span class="lineno">   12</span><span class="comment"> * \par Copyright 1995-2017 Shark Development Team</span></div>
<div class="line"><a id="l00013" name="l00013"></a><span class="lineno">   13</span><span class="comment"> * </span></div>
<div class="line"><a id="l00014" name="l00014"></a><span class="lineno">   14</span><span class="comment"> * &lt;BR&gt;&lt;HR&gt;</span></div>
<div class="line"><a id="l00015" name="l00015"></a><span class="lineno">   15</span><span class="comment"> * This file is part of Shark.</span></div>
<div class="line"><a id="l00016" name="l00016"></a><span class="lineno">   16</span><span class="comment"> * &lt;https://shark-ml.github.io/Shark/&gt;</span></div>
<div class="line"><a id="l00017" name="l00017"></a><span class="lineno">   17</span><span class="comment"> * </span></div>
<div class="line"><a id="l00018" name="l00018"></a><span class="lineno">   18</span><span class="comment"> * Shark is free software: you can redistribute it and/or modify</span></div>
<div class="line"><a id="l00019" name="l00019"></a><span class="lineno">   19</span><span class="comment"> * it under the terms of the GNU Lesser General Public License as published </span></div>
<div class="line"><a id="l00020" name="l00020"></a><span class="lineno">   20</span><span class="comment"> * by the Free Software Foundation, either version 3 of the License, or</span></div>
<div class="line"><a id="l00021" name="l00021"></a><span class="lineno">   21</span><span class="comment"> * (at your option) any later version.</span></div>
<div class="line"><a id="l00022" name="l00022"></a><span class="lineno">   22</span><span class="comment"> * </span></div>
<div class="line"><a id="l00023" name="l00023"></a><span class="lineno">   23</span><span class="comment"> * Shark is distributed in the hope that it will be useful,</span></div>
<div class="line"><a id="l00024" name="l00024"></a><span class="lineno">   24</span><span class="comment"> * but WITHOUT ANY WARRANTY; without even the implied warranty of</span></div>
<div class="line"><a id="l00025" name="l00025"></a><span class="lineno">   25</span><span class="comment"> * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the</span></div>
<div class="line"><a id="l00026" name="l00026"></a><span class="lineno">   26</span><span class="comment"> * GNU Lesser General Public License for more details.</span></div>
<div class="line"><a id="l00027" name="l00027"></a><span class="lineno">   27</span><span class="comment"> * </span></div>
<div class="line"><a id="l00028" name="l00028"></a><span class="lineno">   28</span><span class="comment"> * You should have received a copy of the GNU Lesser General Public License</span></div>
<div class="line"><a id="l00029" name="l00029"></a><span class="lineno">   29</span><span class="comment"> * along with Shark.  If not, see &lt;http://www.gnu.org/licenses/&gt;.</span></div>
<div class="line"><a id="l00030" name="l00030"></a><span class="lineno">   30</span><span class="comment"> *</span></div>
<div class="line"><a id="l00031" name="l00031"></a><span class="lineno">   31</span><span class="comment"> */</span></div>
<div class="line"><a id="l00032" name="l00032"></a><span class="lineno">   32</span><span class="preprocessor">#ifndef SHARK_OBJECTIVEFUNCTIONS_LOOERROR_H</span></div>
<div class="line"><a id="l00033" name="l00033"></a><span class="lineno">   33</span><span class="preprocessor">#define SHARK_OBJECTIVEFUNCTIONS_LOOERROR_H</span></div>
<div class="line"><a id="l00034" name="l00034"></a><span class="lineno">   34</span> </div>
<div class="line"><a id="l00035" name="l00035"></a><span class="lineno">   35</span> </div>
<div class="line"><a id="l00036" name="l00036"></a><span class="lineno">   36</span><span class="preprocessor">#include &lt;<a class="code" href="_abstract_objective_function_8h.html" title="AbstractObjectiveFunction.">shark/ObjectiveFunctions/AbstractObjectiveFunction.h</a>&gt;</span></div>
<div class="line"><a id="l00037" name="l00037"></a><span class="lineno">   37</span><span class="preprocessor">#include &lt;<a class="code" href="_abstract_model_8h.html">shark/Models/AbstractModel.h</a>&gt;</span></div>
<div class="line"><a id="l00038" name="l00038"></a><span class="lineno">   38</span><span class="preprocessor">#include &lt;<a class="code" href="_abstract_loss_8h.html" title="super class of all loss functions">shark/ObjectiveFunctions/Loss/AbstractLoss.h</a>&gt;</span></div>
<div class="line"><a id="l00039" name="l00039"></a><span class="lineno">   39</span><span class="preprocessor">#include &lt;<a class="code" href="_abstract_trainer_8h.html" title="Abstract Trainer Interface.">shark/Algorithms/Trainers/AbstractTrainer.h</a>&gt;</span></div>
<div class="line"><a id="l00040" name="l00040"></a><span class="lineno">   40</span><span class="preprocessor">#include &lt;<a class="code" href="_data_view_8h.html">shark/Data/DataView.h</a>&gt;</span></div>
<div class="line"><a id="l00041" name="l00041"></a><span class="lineno">   41</span><span class="preprocessor">#include &lt;boost/range/algorithm_ext/iota.hpp&gt;</span></div>
<div class="line"><a id="l00042" name="l00042"></a><span class="lineno">   42</span> </div>
<div class="line"><a id="l00043" name="l00043"></a><span class="lineno">   43</span> </div>
<div class="line"><a id="l00044" name="l00044"></a><span class="lineno">   44</span><span class="keyword">namespace </span><a class="code hl_namespace" href="namespaceshark.html" title="AbstractMultiObjectiveOptimizer.">shark</a> {</div>
<div class="line"><a id="l00045" name="l00045"></a><span class="lineno">   45</span> </div>
<div class="line"><a id="l00046" name="l00046"></a><span class="lineno">   46</span><span class="comment"></span> </div>
<div class="line"><a id="l00047" name="l00047"></a><span class="lineno">   47</span><span class="comment">///</span></div>
<div class="line"><a id="l00048" name="l00048"></a><span class="lineno">   48</span><span class="comment">/// \brief Leave-one-out error objective function.</span></div>
<div class="line"><a id="l00049" name="l00049"></a><span class="lineno">   49</span><span class="comment">///</span></div>
<div class="line"><a id="l00050" name="l00050"></a><span class="lineno">   50</span><span class="comment">/// \par</span></div>
<div class="line"><a id="l00051" name="l00051"></a><span class="lineno">   51</span><span class="comment">/// The leave-one-out measure is the average prediction performance of</span></div>
<div class="line"><a id="l00052" name="l00052"></a><span class="lineno">   52</span><span class="comment">/// a learning machine on a dataset, where each sample is predicted by</span></div>
<div class="line"><a id="l00053" name="l00053"></a><span class="lineno">   53</span><span class="comment">/// a machine trained on all but the sample to be predicted. This is an</span></div>
<div class="line"><a id="l00054" name="l00054"></a><span class="lineno">   54</span><span class="comment">/// extreme form of cross-validation, with a fold size of one.</span></div>
<div class="line"><a id="l00055" name="l00055"></a><span class="lineno">   55</span><span class="comment">///</span></div>
<div class="line"><a id="l00056" name="l00056"></a><span class="lineno">   56</span><span class="comment">/// \par</span></div>
<div class="line"><a id="l00057" name="l00057"></a><span class="lineno">   57</span><span class="comment">/// In general the leave-one-out error is costly to compute, since it</span></div>
<div class="line"><a id="l00058" name="l00058"></a><span class="lineno">   58</span><span class="comment">/// requires training of a large number of learning machines. However,</span></div>
<div class="line"><a id="l00059" name="l00059"></a><span class="lineno">   59</span><span class="comment">/// certain machines allow for a more efficient implementation. Refer</span></div>
<div class="line"><a id="l00060" name="l00060"></a><span class="lineno">   60</span><span class="comment">/// to LooErrorCSvm for an example.</span></div>
<div class="line"><a id="l00061" name="l00061"></a><span class="lineno">   61</span><span class="comment">/// \ingroup objfunctions</span></div>
<div class="line"><a id="l00062" name="l00062"></a><span class="lineno">   62</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> ModelTypeT, <span class="keyword">class</span> LabelType = <span class="keyword">typename</span> ModelTypeT::OutputType&gt;</div>
<div class="foldopen" id="foldopen00063" data-start="{" data-end="};">
<div class="line"><a id="l00063" name="l00063"></a><span class="lineno"><a class="line" href="classshark_1_1_loo_error.html">   63</a></span><span class="keyword">class </span><a class="code hl_class" href="classshark_1_1_loo_error.html" title="Leave-one-out error objective function.">LooError</a> : <span class="keyword">public</span> <a class="code hl_class" href="classshark_1_1_abstract_objective_function.html" title="Super class of all objective functions for optimization and learning.">AbstractObjectiveFunction</a>&lt; RealVector, double &gt;</div>
<div class="line"><a id="l00064" name="l00064"></a><span class="lineno">   64</span>{</div>
<div class="line"><a id="l00065" name="l00065"></a><span class="lineno">   65</span><span class="keyword">public</span>:</div>
<div class="line"><a id="l00066" name="l00066"></a><span class="lineno"><a class="line" href="classshark_1_1_loo_error.html#aeebe3f649a655a693566c209f8fde436">   66</a></span>    <span class="keyword">typedef</span> ModelTypeT <a class="code hl_typedef" href="classshark_1_1_loo_error.html#aeebe3f649a655a693566c209f8fde436">ModelType</a>;</div>
<div class="line"><a id="l00067" name="l00067"></a><span class="lineno"><a class="line" href="classshark_1_1_loo_error.html#a3d4e7296d56808b83f609ecb70f121aa">   67</a></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> ModelType::InputType <a class="code hl_typedef" href="classshark_1_1_loo_error.html#a3d4e7296d56808b83f609ecb70f121aa">InputType</a>;</div>
<div class="line"><a id="l00068" name="l00068"></a><span class="lineno"><a class="line" href="classshark_1_1_loo_error.html#ae009af284a0f073b1118fcaeb9a92356">   68</a></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> ModelType::OutputType <a class="code hl_typedef" href="classshark_1_1_loo_error.html#ae009af284a0f073b1118fcaeb9a92356">OutputType</a>;</div>
<div class="line"><a id="l00069" name="l00069"></a><span class="lineno"><a class="line" href="classshark_1_1_loo_error.html#a98fd037674411d450eb935f09319bb40">   69</a></span>    <span class="keyword">typedef</span> <a class="code hl_class" href="classshark_1_1_labeled_data.html" title="Data set for supervised learning.">LabeledData&lt;InputType, LabelType&gt;</a> <a class="code hl_typedef" href="classshark_1_1_loo_error.html#a98fd037674411d450eb935f09319bb40">DatasetType</a>;</div>
<div class="line"><a id="l00070" name="l00070"></a><span class="lineno"><a class="line" href="classshark_1_1_loo_error.html#a5bc94bd972315845cb98d73988f6d908">   70</a></span>    <span class="keyword">typedef</span> <a class="code hl_class" href="classshark_1_1_abstract_trainer.html" title="Superclass of supervised learning algorithms.">AbstractTrainer&lt;ModelType, LabelType&gt;</a> <a class="code hl_typedef" href="classshark_1_1_loo_error.html#a5bc94bd972315845cb98d73988f6d908">TrainerType</a>;</div>
<div class="line"><a id="l00071" name="l00071"></a><span class="lineno"><a class="line" href="classshark_1_1_loo_error.html#a7b1a832c24da5cce462b16c0a6a0566c">   71</a></span>    <span class="keyword">typedef</span> <a class="code hl_class" href="classshark_1_1_abstract_loss.html" title="Loss function interface.">AbstractLoss&lt;LabelType, typename ModelType::OutputType&gt;</a> <a class="code hl_typedef" href="classshark_1_1_loo_error.html#a7b1a832c24da5cce462b16c0a6a0566c">LossType</a>;</div>
<div class="line"><a id="l00072" name="l00072"></a><span class="lineno">   72</span><span class="comment"></span> </div>
<div class="line"><a id="l00073" name="l00073"></a><span class="lineno">   73</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00074" name="l00074"></a><span class="lineno">   74</span><span class="comment">    /// \brief Constructor.</span></div>
<div class="line"><a id="l00075" name="l00075"></a><span class="lineno">   75</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00076" name="l00076"></a><span class="lineno">   76</span><span class="comment">    /// \param  dataset  Full data set for leave-one-out.</span></div>
<div class="line"><a id="l00077" name="l00077"></a><span class="lineno">   77</span><span class="comment">    /// \param  model    Model built on subsets of the data.</span></div>
<div class="line"><a id="l00078" name="l00078"></a><span class="lineno">   78</span><span class="comment">    /// \param  trainer  Trainer for learning on each subset.</span></div>
<div class="line"><a id="l00079" name="l00079"></a><span class="lineno">   79</span><span class="comment">    /// \param  loss     Loss function for judging the validation output.</span></div>
<div class="line"><a id="l00080" name="l00080"></a><span class="lineno">   80</span><span class="comment">    /// \param  meta     Meta object with parameters that influences the process, typically a trainer.</span></div>
<div class="line"><a id="l00081" name="l00081"></a><span class="lineno">   81</span><span class="comment">    ///</span></div>
<div class="foldopen" id="foldopen00082" data-start="{" data-end="}">
<div class="line"><a id="l00082" name="l00082"></a><span class="lineno"><a class="line" href="classshark_1_1_loo_error.html#abf0bc6ef63dc7648e2fc257b7c6587cb">   82</a></span><span class="comment"></span>    <a class="code hl_function" href="classshark_1_1_loo_error.html#abf0bc6ef63dc7648e2fc257b7c6587cb" title="Constructor.">LooError</a>(</div>
<div class="line"><a id="l00083" name="l00083"></a><span class="lineno">   83</span>        <a class="code hl_class" href="classshark_1_1_labeled_data.html">DatasetType</a> <span class="keyword">const</span>&amp; dataset,</div>
<div class="line"><a id="l00084" name="l00084"></a><span class="lineno">   84</span>        <a class="code hl_typedef" href="classshark_1_1_loo_error.html#aeebe3f649a655a693566c209f8fde436">ModelType</a>* model,</div>
<div class="line"><a id="l00085" name="l00085"></a><span class="lineno">   85</span>        <a class="code hl_class" href="classshark_1_1_abstract_trainer.html" title="Superclass of supervised learning algorithms.">TrainerType</a>* trainer,</div>
<div class="line"><a id="l00086" name="l00086"></a><span class="lineno">   86</span>        <a class="code hl_class" href="classshark_1_1_abstract_loss.html" title="Loss function interface.">LossType</a>* loss,</div>
<div class="line"><a id="l00087" name="l00087"></a><span class="lineno">   87</span>        <a class="code hl_class" href="classshark_1_1_i_parameterizable.html" title="Top level interface for everything that holds parameters.">IParameterizable&lt;&gt;</a>* meta = NULL)</div>
<div class="line"><a id="l00088" name="l00088"></a><span class="lineno">   88</span>    : <a class="code hl_variable" href="classshark_1_1_loo_error.html#a5a0ada9191df98c3e76945c933c0baee">m_dataset</a>(dataset)</div>
<div class="line"><a id="l00089" name="l00089"></a><span class="lineno">   89</span>    , <a class="code hl_variable" href="classshark_1_1_loo_error.html#aea70652be0f160c383401a7355f298f0">mep_meta</a>(meta)</div>
<div class="line"><a id="l00090" name="l00090"></a><span class="lineno">   90</span>    , <a class="code hl_variable" href="classshark_1_1_loo_error.html#a381cef0b5509ecb47d8689d7bc31a0af">mep_model</a>(model)</div>
<div class="line"><a id="l00091" name="l00091"></a><span class="lineno">   91</span>    , <a class="code hl_variable" href="classshark_1_1_loo_error.html#ad1255ac86d5d31b56156ee7a4b9a6783">mep_trainer</a>(trainer)</div>
<div class="line"><a id="l00092" name="l00092"></a><span class="lineno">   92</span>    , <a class="code hl_variable" href="classshark_1_1_loo_error.html#a44b42d66c0a82c1605a3051d0641c471">mep_loss</a>(loss)</div>
<div class="line"><a id="l00093" name="l00093"></a><span class="lineno">   93</span>    {</div>
<div class="line"><a id="l00094" name="l00094"></a><span class="lineno">   94</span>        <a class="code hl_variable" href="classshark_1_1_abstract_objective_function.html#ad8888c58fd3f98e73013afb5dd4b2af1">m_features</a> |= <a class="code hl_enumvalue" href="classshark_1_1_abstract_objective_function.html#aadafeb6dfb5b649f321e7b81ac8aad1aad3475b458576c8760f28d8d81f4eda86" title="The function can be evaluated and evalDerivative returns a meaningless value (for example std::numeri...">HAS_VALUE</a>;</div>
<div class="line"><a id="l00095" name="l00095"></a><span class="lineno">   95</span>    }</div>
</div>
<div class="line"><a id="l00096" name="l00096"></a><span class="lineno">   96</span> </div>
<div class="line"><a id="l00097" name="l00097"></a><span class="lineno">   97</span><span class="comment"></span> </div>
<div class="line"><a id="l00098" name="l00098"></a><span class="lineno">   98</span><span class="comment">    /// \brief From INameable: return the class name.</span></div>
<div class="foldopen" id="foldopen00099" data-start="{" data-end="}">
<div class="line"><a id="l00099" name="l00099"></a><span class="lineno"><a class="line" href="classshark_1_1_loo_error.html#a4deb85efd90bada09269d3433e72497a">   99</a></span><span class="comment"></span>    std::string <a class="code hl_function" href="classshark_1_1_loo_error.html#a4deb85efd90bada09269d3433e72497a" title="From INameable: return the class name.">name</a>()<span class="keyword"> const</span></div>
<div class="line"><a id="l00100" name="l00100"></a><span class="lineno">  100</span><span class="keyword">    </span>{</div>
<div class="line"><a id="l00101" name="l00101"></a><span class="lineno">  101</span>        <span class="keywordflow">return</span> <span class="stringliteral">&quot;LooError&lt;&quot;</span></div>
<div class="line"><a id="l00102" name="l00102"></a><span class="lineno">  102</span>                + <a class="code hl_variable" href="classshark_1_1_loo_error.html#a381cef0b5509ecb47d8689d7bc31a0af">mep_model</a>-&gt;name() + <span class="stringliteral">&quot;,&quot;</span></div>
<div class="line"><a id="l00103" name="l00103"></a><span class="lineno">  103</span>                + <a class="code hl_variable" href="classshark_1_1_loo_error.html#ad1255ac86d5d31b56156ee7a4b9a6783">mep_trainer</a>-&gt;<a class="code hl_function" href="classshark_1_1_i_nameable.html#a9893f99314de30cd472e649c235d0db4" title="returns the name of the object">name</a>() + <span class="stringliteral">&quot;,&quot;</span></div>
<div class="line"><a id="l00104" name="l00104"></a><span class="lineno">  104</span>                + <a class="code hl_variable" href="classshark_1_1_loo_error.html#a44b42d66c0a82c1605a3051d0641c471">mep_loss</a>-&gt;<a class="code hl_function" href="classshark_1_1_i_nameable.html#a9893f99314de30cd472e649c235d0db4" title="returns the name of the object">name</a>() + <span class="stringliteral">&quot;&gt;&quot;</span>;</div>
<div class="line"><a id="l00105" name="l00105"></a><span class="lineno">  105</span>    }</div>
</div>
<div class="line"><a id="l00106" name="l00106"></a><span class="lineno">  106</span>    </div>
<div class="foldopen" id="foldopen00107" data-start="{" data-end="}">
<div class="line"><a id="l00107" name="l00107"></a><span class="lineno"><a class="line" href="classshark_1_1_loo_error.html#ac0261f681ff5438e68e8a29fe64265dc">  107</a></span>    std::size_t <a class="code hl_function" href="classshark_1_1_loo_error.html#ac0261f681ff5438e68e8a29fe64265dc" title="Accesses the number of variables.">numberOfVariables</a>()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00108" name="l00108"></a><span class="lineno">  108</span>        <span class="keywordflow">return</span> <a class="code hl_variable" href="classshark_1_1_loo_error.html#aea70652be0f160c383401a7355f298f0">mep_meta</a>-&gt;<a class="code hl_function" href="classshark_1_1_i_parameterizable.html#aed1e8d1d4dbde387e2f6a25141ed3a20" title="Return the number of parameters.">numberOfParameters</a>();</div>
<div class="line"><a id="l00109" name="l00109"></a><span class="lineno">  109</span>    }</div>
</div>
<div class="line"><a id="l00110" name="l00110"></a><span class="lineno">  110</span><span class="comment"></span> </div>
<div class="line"><a id="l00111" name="l00111"></a><span class="lineno">  111</span><span class="comment">    /// Evaluate the leave-one-out error:</span></div>
<div class="line"><a id="l00112" name="l00112"></a><span class="lineno">  112</span><span class="comment">    /// train sub-models, evaluate objective,</span></div>
<div class="line"><a id="l00113" name="l00113"></a><span class="lineno">  113</span><span class="comment">    /// return the average.</span></div>
<div class="foldopen" id="foldopen00114" data-start="{" data-end="}">
<div class="line"><a id="l00114" name="l00114"></a><span class="lineno"><a class="line" href="classshark_1_1_loo_error.html#ac21fc9ca54e8f324cc6136bc5cebb121">  114</a></span><span class="comment"></span>    <span class="keywordtype">double</span> <a class="code hl_function" href="classshark_1_1_loo_error.html#ac21fc9ca54e8f324cc6136bc5cebb121">eval</a>()<span class="keyword"> const </span>{</div>
<div class="line"><a id="l00115" name="l00115"></a><span class="lineno">  115</span>        this-&gt;<a class="code hl_variable" href="classshark_1_1_abstract_objective_function.html#af0942c072be06d0dd4da5ee7067c5777" title="Evaluation counter, default value: 0.">m_evaluationCounter</a>++;</div>
<div class="line"><a id="l00116" name="l00116"></a><span class="lineno">  116</span> </div>
<div class="line"><a id="l00117" name="l00117"></a><span class="lineno">  117</span>        std::size_t ell = <a class="code hl_variable" href="classshark_1_1_loo_error.html#a5a0ada9191df98c3e76945c933c0baee">m_dataset</a>.size();</div>
<div class="line"><a id="l00118" name="l00118"></a><span class="lineno">  118</span>        <a class="code hl_class" href="classshark_1_1_data.html" title="Data container.">Data&lt;OutputType&gt;</a> output;</div>
<div class="line"><a id="l00119" name="l00119"></a><span class="lineno">  119</span>        <span class="keywordtype">double</span> sum = 0.0;</div>
<div class="line"><a id="l00120" name="l00120"></a><span class="lineno">  120</span>        std::vector&lt;std::size_t&gt; indices(ell - 1);</div>
<div class="line"><a id="l00121" name="l00121"></a><span class="lineno">  121</span>        boost::iota(indices,0);</div>
<div class="line"><a id="l00122" name="l00122"></a><span class="lineno">  122</span>        <span class="keywordflow">for</span> (std::size_t i=0; i&lt;ell-1; i++) indices[i] = i+1;</div>
<div class="line"><a id="l00123" name="l00123"></a><span class="lineno">  123</span>        <span class="keywordflow">for</span> (std::size_t i=0; i&lt;ell; i++)</div>
<div class="line"><a id="l00124" name="l00124"></a><span class="lineno">  124</span>        {</div>
<div class="line"><a id="l00125" name="l00125"></a><span class="lineno">  125</span>            <a class="code hl_class" href="classshark_1_1_labeled_data.html">DatasetType</a> train = <a class="code hl_function" href="group__shark__globals.html#ga3c0660922e34389d005bb81e9bde0c18" title="Creates a new dataset from a View.">toDataset</a>(<a class="code hl_function" href="group__shark__globals.html#ga420a47af92d8da0f5e95a7d158521db9" title="Creates a subset of a DataView with elements indexed by indices.">subset</a>(<a class="code hl_variable" href="classshark_1_1_loo_error.html#a5a0ada9191df98c3e76945c933c0baee">m_dataset</a>,indices));</div>
<div class="line"><a id="l00126" name="l00126"></a><span class="lineno">  126</span>            <a class="code hl_variable" href="classshark_1_1_loo_error.html#ad1255ac86d5d31b56156ee7a4b9a6783">mep_trainer</a>-&gt;<a class="code hl_function" href="classshark_1_1_abstract_trainer.html#a71d3fd2567473d746ecb733d7fa28c7e" title="Core of the Trainer interface.">train</a>(*<a class="code hl_variable" href="classshark_1_1_loo_error.html#a381cef0b5509ecb47d8689d7bc31a0af">mep_model</a>, train);</div>
<div class="line"><a id="l00127" name="l00127"></a><span class="lineno">  127</span>            <a class="code hl_typedef" href="classshark_1_1_loo_error.html#ae009af284a0f073b1118fcaeb9a92356">OutputType</a> validation = (*mep_model)(<a class="code hl_variable" href="classshark_1_1_loo_error.html#a5a0ada9191df98c3e76945c933c0baee">m_dataset</a>[i].input);</div>
<div class="line"><a id="l00128" name="l00128"></a><span class="lineno">  128</span>            sum += <a class="code hl_variable" href="classshark_1_1_loo_error.html#a44b42d66c0a82c1605a3051d0641c471">mep_loss</a>-&gt;<a class="code hl_function" href="classshark_1_1_abstract_loss.html#ad57cb10f610d506e522f707563acabb8" title="evaluate the loss for a batch of targets and a prediction">eval</a>(<a class="code hl_variable" href="classshark_1_1_loo_error.html#a5a0ada9191df98c3e76945c933c0baee">m_dataset</a>[i].label, validation);</div>
<div class="line"><a id="l00129" name="l00129"></a><span class="lineno">  129</span>            <span class="keywordflow">if</span> (i &lt; ell - 1) indices[i] = i;</div>
<div class="line"><a id="l00130" name="l00130"></a><span class="lineno">  130</span>        }</div>
<div class="line"><a id="l00131" name="l00131"></a><span class="lineno">  131</span>        <span class="keywordflow">return</span> sum / ell;</div>
<div class="line"><a id="l00132" name="l00132"></a><span class="lineno">  132</span>    }</div>
</div>
<div class="line"><a id="l00133" name="l00133"></a><span class="lineno">  133</span><span class="comment"></span> </div>
<div class="line"><a id="l00134" name="l00134"></a><span class="lineno">  134</span><span class="comment">    /// Evaluate the leave-one-out error for the given</span></div>
<div class="line"><a id="l00135" name="l00135"></a><span class="lineno">  135</span><span class="comment">    /// parameters passed to the meta object (typically</span></div>
<div class="line"><a id="l00136" name="l00136"></a><span class="lineno">  136</span><span class="comment">    /// these parameters need to be optimized in a model</span></div>
<div class="line"><a id="l00137" name="l00137"></a><span class="lineno">  137</span><span class="comment">    /// selection procedure).</span></div>
<div class="foldopen" id="foldopen00138" data-start="{" data-end="}">
<div class="line"><a id="l00138" name="l00138"></a><span class="lineno"><a class="line" href="classshark_1_1_loo_error.html#af232bdbe9573aae2d81d9d574c331425">  138</a></span><span class="comment"></span>    <span class="keywordtype">double</span> <a class="code hl_function" href="classshark_1_1_loo_error.html#af232bdbe9573aae2d81d9d574c331425">eval</a>(<span class="keyword">const</span> RealVector&amp; parameters)<span class="keyword"> const </span>{</div>
<div class="line"><a id="l00139" name="l00139"></a><span class="lineno">  139</span>        <a class="code hl_define" href="_exception_8h.html#a73abb5049a0168d72a48e72dda41708b">SHARK_ASSERT</a>(<a class="code hl_variable" href="classshark_1_1_loo_error.html#aea70652be0f160c383401a7355f298f0">mep_meta</a> != NULL);</div>
<div class="line"><a id="l00140" name="l00140"></a><span class="lineno">  140</span>        <a class="code hl_variable" href="classshark_1_1_loo_error.html#aea70652be0f160c383401a7355f298f0">mep_meta</a>-&gt;<a class="code hl_function" href="classshark_1_1_i_parameterizable.html#ad5e35d1a10ff36fa72ea787baa40e9ad" title="Set the parameter vector.">setParameterVector</a>(parameters);</div>
<div class="line"><a id="l00141" name="l00141"></a><span class="lineno">  141</span>        <span class="keywordflow">return</span> <a class="code hl_function" href="classshark_1_1_loo_error.html#ac21fc9ca54e8f324cc6136bc5cebb121">eval</a>();</div>
<div class="line"><a id="l00142" name="l00142"></a><span class="lineno">  142</span>    }</div>
</div>
<div class="line"><a id="l00143" name="l00143"></a><span class="lineno">  143</span><span class="keyword">protected</span>:</div>
<div class="line"><a id="l00144" name="l00144"></a><span class="lineno"><a class="line" href="classshark_1_1_loo_error.html#a5a0ada9191df98c3e76945c933c0baee">  144</a></span>    <a class="code hl_class" href="classshark_1_1_data_view.html" title="Constant time Element-Lookup for Datasets.">DataView&lt;DatasetType const&gt;</a> <a class="code hl_variable" href="classshark_1_1_loo_error.html#a5a0ada9191df98c3e76945c933c0baee">m_dataset</a>;</div>
<div class="line"><a id="l00145" name="l00145"></a><span class="lineno"><a class="line" href="classshark_1_1_loo_error.html#aea70652be0f160c383401a7355f298f0">  145</a></span>    <a class="code hl_class" href="classshark_1_1_i_parameterizable.html" title="Top level interface for everything that holds parameters.">IParameterizable&lt;&gt;</a>* <a class="code hl_variable" href="classshark_1_1_loo_error.html#aea70652be0f160c383401a7355f298f0">mep_meta</a>;</div>
<div class="line"><a id="l00146" name="l00146"></a><span class="lineno"><a class="line" href="classshark_1_1_loo_error.html#a381cef0b5509ecb47d8689d7bc31a0af">  146</a></span>    <a class="code hl_typedef" href="classshark_1_1_loo_error.html#aeebe3f649a655a693566c209f8fde436">ModelType</a>* <a class="code hl_variable" href="classshark_1_1_loo_error.html#a381cef0b5509ecb47d8689d7bc31a0af">mep_model</a>;</div>
<div class="line"><a id="l00147" name="l00147"></a><span class="lineno"><a class="line" href="classshark_1_1_loo_error.html#ad1255ac86d5d31b56156ee7a4b9a6783">  147</a></span>    <a class="code hl_class" href="classshark_1_1_abstract_trainer.html" title="Superclass of supervised learning algorithms.">TrainerType</a>* <a class="code hl_variable" href="classshark_1_1_loo_error.html#ad1255ac86d5d31b56156ee7a4b9a6783">mep_trainer</a>;</div>
<div class="line"><a id="l00148" name="l00148"></a><span class="lineno"><a class="line" href="classshark_1_1_loo_error.html#a44b42d66c0a82c1605a3051d0641c471">  148</a></span>    <a class="code hl_class" href="classshark_1_1_abstract_loss.html" title="Loss function interface.">LossType</a>* <a class="code hl_variable" href="classshark_1_1_loo_error.html#a44b42d66c0a82c1605a3051d0641c471">mep_loss</a>;</div>
<div class="line"><a id="l00149" name="l00149"></a><span class="lineno">  149</span>};</div>
</div>
<div class="line"><a id="l00150" name="l00150"></a><span class="lineno">  150</span> </div>
<div class="line"><a id="l00151" name="l00151"></a><span class="lineno">  151</span> </div>
<div class="line"><a id="l00152" name="l00152"></a><span class="lineno">  152</span>}</div>
<div class="line"><a id="l00153" name="l00153"></a><span class="lineno">  153</span><span class="preprocessor">#endif</span></div>
</div><!-- fragment --></div><!-- contents -->
</div>
</body>
</html>
